Modelling future refineries on the path to net-zero CO2 emissions

Abstract

Refineries are major emitters of carbon dioxide, thus major mitigation measures are required for this industrial sector. In this research, a model was developed to evaluate mitigation options for refineries. The model is able to capture the interplay between multiple mitigation options and their total combined effect when applied to a refinery. The mitigation options investigated include carbon capture and storage and bio-based feedstock co-processing. Furthermore, the model is capable of quantifying the effect of recovering excess heat available in the refinery to cover the heat demand of the carbon capture unit. The performance indicators calculated by the model include the CO2 mitigation potential and changes in the refinery’s energy demand resulting from application of selected mitigation options. The model was tested through a case study of the Preemraff Lysekil refinery, with a focus on mitigation options for the hydrogen production unit which accounts for 20.6% of the refinery’s total on-site emissions. The results indicate that implementing carbon capture and storage could potentially mitigate 53.5% of the total emissions of this unit. Furthermore, recovery and use of excess heat could potentially cover the full energy demand of the carbon capture unit, thereby increasing the CO2 mitigation potential by 55.7%. The bio-based feedstock co-processing option considered was hydrotreating of lipid-based feedstocks. The method is able to quantify the amount of on-site biogenic CO2 emissions generated within the upgrading process of the bio-based feedstock. The analysis was conducted for hydrotreating of a mixture of light gas oil and 17 wt% rapeseed oil. Compared to the effects of carbon capture and storage applied to the hydrogen production unit, the mitigation potential of the co-processing was around 2.5 times higher whereas the energy demand increase was shown to be only 9.6%. The interplay between the two mitigation options was analysed based on a number of test points. The best trade-off was identified as a low share of applying carbon capture (62.2%) coupled with co-processing (17 wt% of rapeseed oil). Additional analysis was conducted to evaluate the effects of capturing the on-site biogenic emissions. It was revealed that the rate of increase of the energy demand is notably higher than that of the CO2 emissions mitigation potential. This could be moderated if excess heat covers the energy demand of the carbon capture unit.